def to_csv(self, index=False):
'''
Get the JSON representation of this object
:return: JSON string
'''
data_frame = self.data_frame
headers = [str(sub_col) for _, sub_col in data_frame.columns]
headers.insert(0, 'experiment_name')
headers.append('_empty_')
headers.extend(Configuration.get_parameters())
datas = []
for index, row in data_frame.iterrows():
data = []
data.append(str(row.name))
for col_name, sub_col_name in data_frame.columns:
data_value = float(row[col_name][sub_col_name])
# check for NaN
if math.isnan(data_value):
data_value = 0.0
data.append(str(data_value))
data.extend(str(row.name).split('-'))
datas.append(data)
csv_string = ','.join(headers) + '\n'
for row in datas:
csv_string += ','.join(row) + '\n'
return csv_string
def process(self, data_object):
'''
Process a given file
:param data_object: JSON object
:return: Updated data_object reference
'''
super(ExperimentConfig, self).process(data_object)
self.config = data_object
row = []
for param in Configuration.get_parameters():
if param == 'repeat':
continue
if param in data_object:
self.add_column(param)
row.append(data_object[param])
self.add_row(row)
return data_object
def compare_experiments(self, experiment_metric_file_paths):
'''
Run analysis the compares the output from each experiment
:param experiment_metric_file_paths: List of the metric files
for each of the experiments
:return: dict of the metric objects
'''
# pivot data and generate graph for each metric
for variable in Configuration.get_parameters():
if variable == 'repeat':
continue
# get metrics for variable
cmp_exps = MetricManagerComparer(variable)
class_reader = ClassReader([cmp_exps], MetricManager)
finder = FileFinder([class_reader])
finder.process_file_list(self.base_directory,
experiment_metric_file_paths)
for group_name, metric_name, _ in metric_iter(cmp_exps.metric_map):
if group_name == 'variables':
continue
metric_cmp = SummationVariableComparer(cmp_exps, metric_name)
metric_cmp.process(None)
self._set_data(metric_cmp.to_string(True), variable,
group_name, metric_name)
self._set_graph(metric_cmp.create_graph(), variable,
group_name, metric_name)
# get one table of all the values
cmp_exps = MetricManagerComparer('')
class_reader = ClassReader([cmp_exps], MetricManager)
finder = FileFinder([class_reader])
finder.process_file_list(self.base_directory,
experiment_metric_file_paths)
self._set_data(cmp_exps.to_string(), 'all')
